U.S. patent application number 15/638295 was filed with the patent office on 2019-04-04 for cross device bandwidth utilization control.
This patent application is currently assigned to Google Inc.. The applicant listed for this patent is Google Inc.. Invention is credited to Gaurav Bhaya, Aaron Nathaniel Rothman, Robert Stets.
Application Number | 20190104199 15/638295 |
Document ID | / |
Family ID | 65898178 |
Filed Date | 2019-04-04 |
United States Patent
Application |
20190104199 |
Kind Code |
A1 |
Rothman; Aaron Nathaniel ;
et al. |
April 4, 2019 |
CROSS DEVICE BANDWIDTH UTILIZATION CONTROL
Abstract
A system of multi-modal transmission of packetized data in a
voice activated data packet based computer network environment is
provided. A natural language processor component can parse an input
audio signal to identify a request and a trigger keyword. Based on
the input audio signal, a direct action application programming
interface can generate a first action data structure, and a content
selector component can select a content item based on a count
reaches a target number. An interface management component can
identify first and second candidate interfaces, and respective
resource utilization values. The interface management component can
select, based on the resource utilization values, the first
candidate interface to present the content item.
Inventors: |
Rothman; Aaron Nathaniel;
(Sunnyvale, CA) ; Bhaya; Gaurav; (Sunnyvale,
CA) ; Stets; Robert; (Mountain View, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Google Inc. |
Mountain View |
CA |
US |
|
|
Assignee: |
Google Inc.
Mountain View
CA
|
Family ID: |
65898178 |
Appl. No.: |
15/638295 |
Filed: |
June 29, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13441298 |
Apr 6, 2012 |
9922334 |
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15638295 |
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15395703 |
Dec 30, 2016 |
10032452 |
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13441298 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04L 43/0805 20130101;
H04L 67/327 20130101; G06F 16/243 20190101; H04L 67/42 20130101;
G06Q 30/02 20130101; H04L 67/04 20130101; H04L 67/12 20130101; G06Q
30/0275 20130101 |
International
Class: |
H04L 29/08 20060101
H04L029/08; H04L 12/26 20060101 H04L012/26; G06F 17/30 20060101
G06F017/30 |
Claims
1.-20. (canceled)
21. A system to provide content to computing devices in an online
computer network environment, comprising a data processing system
to: receive an audio-based request from a computing device, the
audio-based request comprising a device identifier associated with
the computing device and the audio-based request detected at the
computing device; receive selection criteria comprising device
identifier characteristics and the selection criteria associated
with a digital component; identify a plurality of digital
components associated with the digital component; determine a count
representing a number of the plurality of digital components
previously transmitted to the computing device; receive a target
number of the plurality of digital components previously
transmitted to the computing device; determine a probability the
count reaches the target number within a predetermined time
interval; select a candidate digital component based on the
probability and selection criteria; and transmit the candidate
digital component to the computing device.
22. The system of claim 21, comprising the data processing system
to: select, based on the selection criteria, an exposure model; and
determine, by the exposure model, the probability the count reaches
the target number.
23. The system of claim 21, comprising the data processing system
to: identify an exposure interval based on the selection criteria;
determine a second probability the computing device displays the
candidate digital component from the exposure interval; and select
the candidate digital component based on the second
probability.
24. The system of claim 21, comprising: a natural language
processor component to: receive, via an interface of the data
processing system, data packets comprising the audio-based request;
identify, from the audio-based request, a request and a trigger
keyword corresponding to the request; a direct action application
programming interface to generate, based on at least one of the
request and the trigger keyword, a first action data structure; and
a content selector component to select the candidate digital
component based on the first action data structure.
25. The system of claim 21, comprising an interface management
component to: poll a plurality of interfaces to identify a first
candidate interface of the computing device and a second candidate
interface of a second computing device; determine a first resource
utilization value for the first candidate interface and a second
resource utilization value for the second candidate interface, the
first resource utilization value and the second resource
utilization value based on at least one of a battery status,
processor utilization, memory utilization, an interface parameter,
and network bandwidth utilization; and select to transmit the
candidate digital component to the computing device based on the
first resource utilization value and the second resource
utilization value.
26. The system of claim 21, comprising an interface management
component to: poll a plurality of interfaces to identify a first
candidate interface of the computing device and a second candidate
interface of a second computing device; transmit the candidate
digital component to the second computing device.
27. The system of claim 21, comprising: an interface management
component to: poll a plurality of interfaces to identify a first
candidate interface of the computing device and a second candidate
interface of a second computing device; transmit, responsive to a
second probability being above a predetermined threshold, the
candidate digital component to the second computing device; the
data processing system to: determine a second count of a number of
the plurality of digital components previously transmitted to the
second computing device; and determine the second probability a
combination of the count and the second count reaches the target
number with the predetermined time interval.
28. The system of claim 21, comprising an interface management
component to: poll a plurality of interfaces of the computing
device; select, based on a resource utilization value of plurality
of interfaces, a candidate interface; and transmit the candidate
digital component to the candidate interface of the computing
device.
29. The system of claim 28, wherein the plurality of interfaces
includes at least one of a display screen, an audio interface, a
vibration interface, an email interface, a push notification
interface, a mobile computing device interface, a portable
computing device application, a content slot on an online document,
a chat application, mobile computing device application, a laptop,
a watch, a virtual reality headset, and a speaker.
30. The system of claim 21, comprising an interface management
component to: poll a plurality of candidate interfaces associated
with the computing device; determine a distance between each of the
plurality of candidate interfaces and the computing device; and
select the candidate digital component based on the distance
between each of the plurality of candidate interfaces and the
computing device.
31. A method to provide content to computing devices in an online
computer network environment, comprising: receiving, by a data
processing system, an audio-based request from a computing device,
the audio-based request comprising a device identifier associated
with the computing device and the audio-based request detected at
the computing device; receiving, by the data processing system,
selection criteria comprising device identifier characteristics and
the selection criteria associated with a digital component;
identifying, by the data processing system, a plurality of digital
components associated with the digital component; determining, by
the data processing system, a count representing a number of the
plurality of digital components previously transmitted to the
computing device; receiving, by the data processing system, a
target number of the plurality of digital components previously
transmitted to the computing device; determining, by the data
processing system, a probability the count reaches the target
number within a predetermined time interval; selecting, by the data
processing system, a candidate digital component based on the
probability and selection criteria; and transmitting, by the data
processing system, the candidate digital component to the computing
device.
32. The method of claim 31, comprising: selecting, based on the
selection criteria, an exposure model; and determining, by the
exposure model, the probability the count reaches the target
number.
33. The method of claim 31, comprising: identifying an exposure
interval based on the selection criteria; determining a second
probability the computing device displays the candidate digital
component from the exposure interval; and selecting the candidate
digital component based on the second probability.
34. The method of claim 31, comprising: receiving, by a natural
language processor component executed by the data processing
system, via an interface of the data processing system, data
packets comprising the audio-based request; identifying, by the
natural language processor component, from the audio-based request,
a request and a trigger keyword corresponding to the request;
generating, by a direct action application programming interface of
the data processing system, based on at least one of the request
and the trigger keyword, a first action data structure; and
selecting, by a content selector component, the candidate digital
component based on the first action data structure.
35. The method of claim 31, comprising: polling, by an interface
management component of the data processing system, a plurality of
interfaces to identify a first candidate interface of the computing
device and a second candidate interface of a second computing
device; determining, by the interface management component, a first
resource utilization value for the first candidate interface and a
second resource utilization value for the second candidate
interface, the first resource utilization value and the second
resource utilization value based on at least one of a battery
status, processor utilization, memory utilization, an interface
parameter, and network bandwidth utilization; and selecting, by the
interface management component, to transmit the candidate digital
component to the computing device based on the first resource
utilization value and the second resource utilization value.
36. The method of claim 31, comprising: polling, by the interface
management component of the data processing system, a plurality of
interfaces to identify a first candidate interface of the computing
device and a second candidate interface of a second computing
device; transmitting, by the interface management component, the
candidate digital component to the second computing device.
37. The method of claim 31, comprising: polling, by the interface
management component of the data processing system, a plurality of
interfaces to identify a first candidate interface of the computing
device and a second candidate interface of a second computing
device; determining, by the data processing system a second count
of a number of the plurality of digital components previously
transmitted to the second computing device; determining, by the
data processing system, a second probability a combination of the
count and the second count reaches the target number with the
predetermined time interval; transmitting, responsive to the second
probability being above a predetermined threshold and by the
interface management component, the candidate digital component to
the second computing device.
38. The method of claim 31, comprising: polling, by an interface
management component, a plurality of interfaces of the computing
device; selecting, based on a resource utilization value of
plurality of interfaces, a candidate interface; and transmitting
the candidate digital component to the candidate interface of the
computing device.
39. The method of claim 38, wherein the plurality of interfaces
includes at least one of a display screen, an audio interface, a
vibration interface, an email interface, a push notification
interface, a mobile computing device interface, a portable
computing device application, a content slot on an online document,
a chat application, mobile computing device application, a laptop,
a watch, a virtual reality headset, and a speaker.
40. The method of claim 31, comprising: polling, by an interface
management component, a plurality of candidate interfaces
associated with the computing device; determining, by the interface
management component, a distance between each of the plurality of
candidate interfaces and the computing device; and selecting, by
the interface management component, the candidate digital component
based on the distance between each of the plurality of candidate
interfaces and the computing device.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The present application claims the benefit of priority under
35 U.S.C. .sctn. 120 as a continuation-in-part of U.S. patent
application Ser. No. 13/441,298, filed Apr. 6, 2012. The present
application also claims the benefit of priority under 35 U.S.C.
.sctn. 120 as a continuation-in-part of U.S. patent application
Ser. No. 15/395,703, filed Dec. 30, 2016. Each of the foregoing
applications is hereby incorporated by reference in their
entirety.
BACKGROUND
[0002] Excessive network transmissions, packet-based or otherwise,
of network traffic data between computing devices can prevent a
computing device from properly processing the network traffic data,
completing an operation related to the network traffic data, or
timely responding to the network traffic data. The excessive
network transmissions of network traffic data can also complicate
data routing or degrade the quality of the response if the
responding computing device is at or above its processing capacity,
which may result in inefficient bandwidth utilization. The control
of network transmissions corresponding to content item objects can
be complicated by the large number of content item objects that can
initiate network transmissions of network traffic data between
computing devices.
SUMMARY
[0003] At least one aspect of the disclosure is directed to a
system to provide content to computing devices in an online
computer network environment. The system includes a data processing
system to receive an audio-based request from a computing device.
The audio-based request can include a device identifier associated
with the computing device. The audio-based request can be detected
at the computing device. The data processing system can receive
selection criteria that can include device identifier
characteristics. The selection criteria can be associated with a
digital component. The data processing system can identify a
plurality of digital components associated with a digital
component. The data processing system can determine a count
representing a number of the plurality of digital components
previously transmitted to the computing device. The data processing
system can receive a target number of the plurality of digital
components previously transmitted to the computing device. The data
processing system can determine a probability the count reaches the
target number within a predetermined time interval. The data
processing system can select a candidate digital component based on
the probability and selection criteria. The data processing system
can transmit the candidate digital component to the computing
device.
[0004] At least one aspect of the disclosure is directed to a
method to provide content to computing devices in an online
computer network environment. The method can include receiving, by
a data processing system, an audio-based request from a computing
device. The audio-based request can include a device identifier
that can be associated with the computing device. The audio-based
request can be detected at the computing device. The method can
include receiving, by the data processing system, selection
criteria that can include device identifier characteristics. The
selection criteria can be associated with a digital component. The
method can include identifying, by the data processing system, a
plurality of digital components associated with the digital
component. The method can include determining, by the data
processing system, a count representing a number of the plurality
of digital components previously transmitted to the computing
device. The method can include receiving, by the data processing
system, a target number of the plurality of digital components
previously transmitted to the computing device. The method can
include determining, by the data processing system, a probability
the count reaches the target number within a predetermined time
interval. The method can include selecting, by the data processing
system, a candidate digital component based on the probability and
selection criteria. The method can include transmitting, by the
data processing system, the candidate digital component to the
computing device.
[0005] These and other aspects and implementations are discussed in
detail below. The foregoing information and the following detailed
description include illustrative examples of various aspects and
implementations, and provide an overview or framework for
understanding the nature and character of the claimed aspects and
implementations. The drawings provide illustration and a further
understanding of the various aspects and implementations, and are
incorporated in and constitute a part of this specification.
BRIEF DESCRIPTION OF THE DRAWINGS
[0006] The accompanying drawings are not intended to be drawn to
scale. Like reference numbers and designations in the various
drawings indicate like elements. For purposes of clarity, not every
component may be labeled in every drawing. In the drawings:
[0007] FIG. 1A is an example of a block diagram of a computer
system in accordance with a described implementation.
[0008] FIG. 1B depicts a system to of multi-modal transmission of
packetized data in a voice activated computer network
environment;
[0009] FIG. 1C depicts a flow diagram for multi-modal transmission
of packetized data in a voice activated computer network
environment;
[0010] FIG. 2 is an illustration of an example system for serving
digital components in accordance with a described
implementation.
[0011] FIG. 3 is an illustration of an example interface for a
service provider in accordance with a described implementation.
[0012] FIG. 4 is an example of a system for updating the device
identifier in accordance with a described implementation.
[0013] FIG. 5 is an example of a flow diagram for serving digital
components in accordance with a described implementation.
[0014] FIG. 6 is a block diagram illustrating an example method to
provide digital components in an online computer network.
[0015] FIG. 7 is a block diagram illustrating a general
architecture for a computer system that may be employed to
implement elements of the systems and methods described and
illustrated herein.
[0016] Like reference numbers and designations in the various
drawings indicate like elements.
DETAILED DESCRIPTION
[0017] Following below are more detailed descriptions of various
concepts related to, and implementations of, methods, apparatuses,
and systems for multi-modal transmission of packetized data in a
voice activated data packet based computer network environment. The
various concepts introduced above and discussed in greater detail
below may be implemented in any of numerous ways.
[0018] Systems and methods of the present disclosure relate
generally to a data processing system that identifies an optimal
transmission modality for data packet (or other protocol based)
transmission in a voice activated computer network environment. The
data processing system can improve the efficiency and effectiveness
of data packet transmission over one or more computer networks by,
for example, selecting a transmission modality from a plurality of
options for data packet routing through a computer network of
content items to one or more client computing device, or to
different interfaces (e.g., different apps or programs) of a single
client computing device. In some implementations, digital
components are transmitted to and displayed by computing device a
predetermined number of times to achieve an outcome. For example, a
digital component (or a group of related digital components) may
need to be displayed five times within a given time interval such
that a user remembers the subject matter of the digital components.
Content items can also be referred to as digital components. In
some implementations, a digital component can be a component of a
content item. The data processing system can also improve the
efficiency and effectiveness of the data packet transmissions over
one of more computer networks by, for example, determining not to
transmit digital components to a computing device. For example, the
data processing system can select to not transmit a digital
component to a computing device, and save bandwidth and
computational resources, if the data processing system determines
the digital component will not be display the predetermined number
of times to achieve the outcome. The data processing system can
also select digital components such that the digital components are
presented the predetermined number of times, such that bandwidth is
not wasted by transmitted digital components that have little
chance of reaching the predetermined number of exposure times.
[0019] Data packets or other protocol based signals corresponding
to the selected operations can be routed through a computer network
between multiple computing devices. For example, the data
processing system can route a content item to a different interface
than an interface from which a request was received. The different
interface can be on the same client computing device or a different
client computing device from which a request was received. The data
processing system can select at least one candidate interface from
a plurality of candidate interfaces for content item transmission
to a client computing device. The candidate interfaces can be
determined based on technical or computing parameters such as
processor capability or utilization rate, memory capability or
availability, battery status, available power, network bandwidth
utilization, interface parameters or other resource utilization
values. By selecting an interface to receive and provide the
content item for rendering from the client computing device based
on candidate interfaces or utilization rates associated with the
candidate interfaces, the data processing system can reduce network
bandwidth usage, latency, or processing utilization or power
consumption of the client computing device that renders the content
item. This saves processing power and other computing resources
such as memory, reduces electrical power consumption by the data
processing system and the reduced data transmissions via the
computer network reduces bandwidth requirements and usage of the
data processing system.
[0020] The systems and methods described herein can include a data
processing system that receives an input audio query, which can
also be referred to as an input audio signal. From the input audio
query the data processing system can identify a request and a
trigger keyword corresponding to the request. Based on the trigger
keyword or the request, the data processing system can generate a
first action data structure. For example, the first action data
structure can include an organic response to the input audio query
received from a client computing device, and the data processing
system can provide the first action data structure to the same
client computing device for rendering as audio output via the same
interface from which the request was received.
[0021] The data processing system can also select at least one
content item based on the trigger keyword or the request. The data
processing system can identify or determine a plurality of
candidate interfaces for rendering of the content item(s). The
interfaces can include one or more hardware or software interfaces,
such as display screens, audio interfaces, speakers, applications
or programs available on the client computing device that
originated the input audio query, or on different client computing
devices. The interfaces can include java script slots for online
documents for the insertion of content items, as well as push
notification interfaces. The data processing system can determine
utilization values for the different candidate interfaces. The
utilization values can indicate power, processing, memory,
bandwidth, or interface parameter capabilities, for example. Based
on the utilization values for the candidate interfaces the data
processing system can select a candidate interface as a selected
interface for presentation or rendering of the content item. For
example, the data processing system can convert or provide the
content item for delivery in a modality compatible with the
selected interface. The selected interface can be an interface of
the same client computing device that originated the input audio
signal or a different client computing device. By routing data
packets via a computing network based on utilization values
associated with a candidate interface, the data processing system
selects a destination for the content item in a manner that can use
the least amount of processing power, memory, or bandwidth from
available options, or that can conserve power of one or more client
computing devices.
[0022] The data processing system can provide the content item or
the first action data structure by packet or other protocol based
data message transmission via a computer network to a client
computing device. The output signal can cause an audio driver
component of the client computing device to generate an acoustic
wave, e.g., an audio output, which can be output from the client
computing device. The audio (or other) output can correspond to the
first action data structure or to the content item. For example,
the first action data structure can be routed as audio output, and
the content item can be routed as a text based message. By routing
the first action data structure and the content item to different
interfaces, the data processing system can conserve resources
utilized by each interface, relative to providing both the first
action data structure and the content item to the same interface.
This results in fewer data processing operations, less memory
usage, or less network bandwidth utilization by the selected
interfaces (or their corresponding devices) than would be the case
without separation and independent routing of the first action data
structure and the content item.
[0023] Service Providers can determine goals for exposure to
certain digital components or groups of digital components within
their content campaigns. Service Providers may also determine a
strategy for what times to serve the digital components to meet
their goals for exposure. The strategy may be based on previous
exposures of the digital components to the users.
[0024] The exposures may be determined by a number of devices,
e.g., a set-top box, a television, a web page, etc. used to serve
the digital components. The devices may include a database to store
the number of exposures and the time of exposure.
[0025] Based on the number of exposures of digital components,
service providers can determine or update strategies for their
proposed, e.g., yet to be served, digital components. For example,
service providers concerned with delivering a message believe that
users may need to be exposed to the message a minimum number of
times, in a given period of time, before the user is aware of the
message. Although a click would count as a recognition of the
message, clicks are not a reliable source to estimate the minimum
number of exposures, e.g., clicks are infrequent and do not
acknowledge every time a user is exposed to the message and does
not click on the message.
[0026] In a general overview, the service provider can determine a
minimum number of exposures for an interval of time. The service
provider may also determine a maximum aggregate bid value for each
user. A digital component server determines the probability that a
user will meet the minimum number of exposures within the interval
of time. Given the probability, the digital component server
adjusts bidding within the service provider's maximum aggregate bid
value for each user that meets the minimum number of exposures
within the interval of time.
[0027] FIG. 1A is a block diagram of a computer system 100 in
accordance with a described implementation. System 100 includes
client computing device 102, which may communicate with other
computing devices via a network 106. For example, client computing
device 102 may communicate with one or more content sources ranging
from a content provider computing device 108 up to an nth content
source 110. Content provider computing devices 108 may provide
webpages and/or media content (e.g., audio, video, and other forms
of digital content) to client computing devices 102. System 100 may
include a data processing system 104, which provides digital
component data to other computing devices over network 106.
[0028] Network 106 may be any form of computer network that relays
information between client computing device 102, data processing
system 104, and content provider computing devices 108. For
example, network 106 may include the Internet and/or other types of
data networks, such as a local area network (LAN), a wide area
network (WAN), a cellular network, satellite network, or other
types of data networks. Network 106 may include any number of
computing devices (e.g., computer, servers, routers, network
switches, etc.) that are configured to receive and/or transmit data
within network 106. Network 106 may include any number of hardwired
and/or wireless connections. For example, client computing device
102 may communicate wirelessly (e.g., via WiFi, cellular, radio,
etc.) with a transceiver that is hardwired (e.g., via a fiber optic
cable, a CAT5 cable, etc.) to other computing devices in network
106.
[0029] Client computing device 102 may be any number of different
user electronic devices configured to communicate via network 106
(e.g., a laptop computer, a desktop computer, a tablet computer, a
smartphone, a digital video recorder, a set-top box for a
television, a video game console, etc.). Client computing device
102 is shown to include a processor 112 and a memory 114, e.g., a
processing circuit. Memory 114 stores machine instructions that,
when executed by processor 112, cause processor 112 to perform one
or more of the operations described herein. Processor 112 may
include a microprocessor, application-specific integrated circuit
(ASIC), field-programmable gate array (FPGA), etc., or combinations
thereof. Memory 114 may include, but is not limited to, electronic,
optical, magnetic, or any other storage or transmission device
capable of providing processor 112 with program instructions.
Memory 114 may include a floppy disk, CD-ROM, DVD, magnetic disk,
memory chip, ASIC, FPGA, read-only memory (ROM), random-access
memory (RAM), electrically-erasable ROM (EEPROM),
erasable-programmable ROM (EPROM), flash memory, optical media, or
any other suitable memory from which processor 112 can read
instructions. The instructions may include code from any suitable
computer-programming language such as, but not limited to, C, C++,
C#, Java, JavaScript, Perl, Python and Visual Basic.
[0030] Client computing device 102 may include one or more user
interface devices. In general, a user interface device refers to
any electronic device that conveys data to a user by generating
sensory information (e.g., a visualization on a display, one or
more sounds, etc.) and/or converts received sensory information
from a user into electronic signals (e.g., a keyboard, a mouse, a
pointing device, a touch screen display, a microphone, etc.). The
one or more user interface devices may be internal to a housing of
client computing device 102 (e.g., a built-in display, microphone,
etc.) or external to the housing of client computing device 102
(e.g., a monitor connected to client computing device 102, a
speaker connected to client computing device 102, etc.), according
to various implementations. For example, client computing device
102 may include an electronic display 116, which visually displays
webpages using webpage data received from content provider
computing devices 108 and/or from data processing system 104.
[0031] Content provider computing devices 108 are electronic
devices connected to network 106 and provide media content to
client computing device 102. For example, content provider
computing devices 108 may be computer servers (e.g., FTP servers,
file sharing servers, web servers, etc.) or other devices that
include a processing circuit. Media content may include, but is not
limited to, webpage data, a movie, a sound file, pictures, and
other forms of data. Similarly, data processing system 104 may
include a processing circuit including a processor 112 and a memory
114. In some implementations, data processing system 104 may
include several computing devices (e.g., a data center, a network
of servers, etc.). In such a case, the various devices of data
processing system 104 may comprise a processing circuit (e.g.,
processor 112 represents the collective processors of the devices
and memory 114 represents the collective memories of the
devices).
[0032] Data processing system 104 may provide digital components to
client computing device 102 via network 106. For example, content
provider computing device 108 may provide a webpage to client
computing device 102, in response to receiving a request for a
webpage from client computing device 102. In some implementations,
a digital component from data processing system 104 may be provided
to client computing device 102 indirectly. For example, content
provider computing device 108 may receive digital component data
from data processing system 104 and use the digital component as
part of the webpage data provided to client computing device 102.
In other implementations, a digital component from data processing
system 104 may be provided to client computing device 102 directly.
For example, content provider computing device 108 may provide
webpage data to client computing devices 102 that includes a
command to retrieve a digital component from data processing system
104. On receipt of the webpage data, client computing device 102
may retrieve a digital component from data processing system 104
based on the command and display the digital component when the
webpage is rendered on display 116.
[0033] According to various implementations, a user of client
computing device 102 may search for, access, etc. various documents
(e.g., web pages, web sites, articles, images, video, etc.) using a
search engine via network 106. The web pages may be displayed as a
search result from a search engine query containing search terms or
keywords. Search engine queries may allow the user to enter a
search term or keyword into the search engine to execute a document
search. Search engines may be stored in memory 114 of data
processing system 104 and may be accessible with client computing
device 102. The result of an executed website search on a search
engine may include a display on a search engine document of links
to websites. Executed search engine queries may result in the
display of digital component data generated and transmitted from
data processing system 104. In some cases, search engines contract
with service providers to display digital component to users of the
search engine in response to certain search engine queries.
[0034] In other implementations, digital component may be displayed
in a publication (e.g., a third-party web page) as in a display
network. For example, a number of web pages and applications may
show relevant digital components. The digital components may be
matched to the web pages and other placements, such as mobile
computing applications, according to relevant content or themes of
the web pages. Specific web pages about specific topics may display
the digital component. The digital component may be shown to all
the web pages or a select number of web pages.
[0035] In another implementation, service providers may purchase or
bid on the search terms such as keyword entries entered by users
into a document such as a search engine. When the search term or
keyword are entered into the document, then digital component data
such as links to a service provider website may be displayed to the
user. In some implementations, data processing system 104 may use
an auction model that generates a digital component. Service
Providers may bid on keywords using the auction model. The auction
model may also be adjusted to reflect the maximum amount a service
provider is willing to spend so that a user is exposed to a digital
component a minimum number of times.
[0036] FIG. 1B depicts an example system 100 to for multi-modal
transmission of packetized data in a voice activated data packet
(or other protocol) based computer network environment. The system
100 can include at least one data processing system 104. The data
processing system 104 can include at least one server having at
least one processor. For example, the data processing system 104
can include a plurality of servers located in at least one data
center or server farm. The data processing system 104 can
determine, from an audio input signal a request and a trigger
keyword associated with the request. Based on the request and
trigger keyword the data processing system 104 can determine or
select at least one action data structure, and can select at least
one content item (and initiate other actions as described herein).
The data processing system 104 can identify candidate interfaces
for rendering of the action data structures or the content items,
and can provide the action data structures or the content items for
rendering by one or more candidate interfaces on one or more client
computing devices based on resource utilization values for or of
the candidate interfaces, for example, as part of a voice activated
communication or planning system. The action data structures (or
the content items) can include one or more audio files that when
rendered provide an audio output or acoustic wave. The action data
structures or the content items can include other content (e.g.,
text, video, or image content) in addition to audio content.
[0037] The data processing system 104 can include multiple,
logically-grouped servers and facilitate distributed computing
techniques. The logical group of servers may be referred to as a
data center, server farm or a machine farm. The servers can be
geographically dispersed. A data center or machine farm may be
administered as a single entity, or the machine farm can include a
plurality of machine farms. The servers within each machine farm
can be heterogeneous--one or more of the servers or machines can
operate according to one or more type of operating system platform.
The data processing system 104 can include servers in a data center
that are stored in one or more high-density rack systems, along
with associated storage systems, located for example, in an
enterprise data center. The data processing system 104 with
consolidated servers in this way can improve system manageability,
data security, the physical security of the system, and system
performance by locating servers and high-performance storage
systems on localized high-performance networks. Centralization of
all or some of the data processing system 104 components, including
servers and storage systems, and coupling them with advanced system
management tools allows more efficient use of server resources,
which saves power and processing requirements and reduces bandwidth
usage.
[0038] The data processing system 104 can include at least one
natural language processor (NLP) component 110, at least one
interface 115, at least one prediction component 120, at least one
content selector component 125, at least one audio signal generator
component 130, at least one direct action application programming
interface (API) 135, at least one interface management component
140, and at least one data repository 145. The NLP component 110,
interface 115, prediction component 120, content selector component
125, audio signal generator component 130, direct action API 135,
and interface management component 140 can each include at least
one processing unit, server, virtual server, circuit, engine,
agent, appliance, or other logic device such as programmable logic
arrays configured to communicate with the data repository 145 and
with other computing devices (e.g., at least one client computing
device 102, at least one content provider computing device 108, or
at least one service provider computing device 160) via the at
least one computer network 106. The network 106 can include
computer networks such as the internet, local, wide, metro or other
area networks, intranets, satellite networks, other computer
networks such as voice or data mobile phone communication networks,
and combinations thereof.
[0039] The network 106 can include or constitute a display network,
e.g., a subset of information resources available on the internet
that are associated with a content placement or search engine
results system, or that are eligible to include third party content
items as part of a content item placement campaign. The network 106
can be used by the data processing system 104 to access information
resources such as web pages, web sites, domain names, or uniform
resource locators that can be presented, output, rendered, or
displayed by the client computing device 102. For example, via the
network 106 a user of the client computing device 102 can access
information or data provided by the data processing system 104, the
content provider computing device 108 or the service provider
computing device 160.
[0040] The network 106 can include, For example, a point-to-point
network, a broadcast network, a wide area network, a local area
network, a telecommunications network, a data communication
network, a computer network, an ATM (Asynchronous Transfer Mode)
network, a SONET (Synchronous Optical Network) network, a SDH
(Synchronous Digital Hierarchy) network, a wireless network or a
wireline network, and combinations thereof. The network 106 can
include a wireless link, such as an infrared channel or satellite
band. The topology of the network 106 may include a bus, star, or
ring network topology. The network 106 can include mobile telephone
networks using any protocol or protocols used to communicate among
mobile devices, including advanced mobile phone protocol ("AMPS"),
time division multiple access ("TDMA"), code-division multiple
access ("CDMA"), global system for mobile communication ("GSM"),
general packet radio services ("GPRS") or universal mobile
telecommunications system ("UMTS"). Different types of data may be
transmitted via different protocols, or the same types of data may
be transmitted via different protocols.
[0041] The client computing device 102, the content provider
computing device 108, and the service provider computing device 160
can each include at least one logic device such as a computing
device having a processor to communicate with each other or with
the data processing system 104 via the network 106. The client
computing device 102, the content provider computing device 108,
and the service provider computing device 160 can each include at
least one server, processor or memory, or a plurality of
computation resources or servers located in at least one data
center. The client computing device 102, the content provider
computing device 108, and the service provider computing device 160
can each include at least one computing device such as a desktop
computer, laptop, tablet, personal digital assistant, smartphone,
portable computer, server, thin client computer, virtual server, or
other computing device.
[0042] The client computing device 102 can include at least one
sensor 151, at least one transducer 152, at least one audio driver
153, and at least one speaker 154. The sensor 151 can include a
microphone or audio input sensor. The transducer 152 can convert
the audio input into an electronic signal, or vice-versa. The audio
driver 153 can include a script or program executed by one or more
processors of the client computing device 102 to control the sensor
151, the transducer 152 or the audio driver 153, among other
components of the client computing device 102 to process audio
input or provide audio output. The speaker 154 can transmit the
audio output signal.
[0043] The client computing device 102 can be associated with an
end user that enters voice queries as audio input into the client
computing device 102 (via the sensor 151) and receives audio output
in the form of a computer generated voice that can be provided from
the data processing system 104 (or the content provider computing
device 108 or the service provider computing device 160) to the
client computing device 102, output from the speaker 154. The audio
output can correspond to an action data structure received from the
direct action API 135, or a content item selected by the content
selector component 125. The computer generated voice can include
recordings from a real person or computer generated language.
[0044] The content provider computing device 108 (or the data
processing system 104 or service provider computing device 160) can
provide audio based content items or action data structures for
display by the client computing device 102 as an audio output. The
action data structure or content item can include an organic
response or offer for a good or service, such as a voice based
message that states: "Today it will be sunny and 80 degrees at the
beach" as an organic response to a voice-input query of "Is today a
beach day?". The data processing system 104 (or other system 100
component such as the content provider computing device 108 can
also provide a content item as a response, such as a voice or text
message based content item offering sunscreen.
[0045] The content provider computing device 108 or the data
repository 145 can include memory to store a series of audio action
data structures or content items that can be provided in response
to a voice based query. The action data structures and content
items can include packet based data structures for transmission via
the network 106. The content provider computing device 108 can also
provide audio or text based content items (or other content items)
to the data processing system 104 where they can be stored in the
data repository 145. The data processing system 104 can select the
audio action data structures or text based content items and
provide (or instruct the content provider computing device 108 to
provide) them to the same or different client computing devices 102
responsive to a query received from one of those client computing
devices 102. The audio based action data structures can be
exclusively audio or can be combined with text, image, or video
data. The content items can be exclusively text or can be combined
with audio, image or video data.
[0046] The service provider computing device 160 can include at
least one service provider natural language processor (NLP)
component 161 and at least one service provider interface 162. The
service provider NLP component 161 (or other components such as a
direct action API of the service provider computing device 160) can
engage with the client computing device 102 (via the data
processing system 104 or bypassing the data processing system 104)
to create a back-and-forth real-time voice or audio based
conversation (e.g., a session) between the client computing device
102 and the service provider computing device 160. For example, the
service provider interface 162 can receive or provide data messages
(e.g., action data structures or content items) to the direct
action API 135 of the data processing system 104. The direct action
API 135 can also generate the action data structures independent
from or without input from the service provider computing device
160. The service provider computing device 160 and the content
provider computing device 108 can be associated with the same
entity. For example, the content provider computing device 108 can
create, store, or make available content items for beach relates
services, such as sunscreen, beach towels or bathing suits, and the
service provider computing device 160 can establish a session with
the client computing device 102 to respond to a voice input query
about the weather at the beach, directions for a beach, or a
recommendation for an area beach, and can provide these content
items to the end user of the client computing device 102 via an
interface of the same client computing device 102 from which the
query was received, a different interface of the same client
computing device 102, or an interface of a different client
computing device. The data processing system 104, via the direct
action API 135, the NLP component 110 or other components can also
establish the session with the client computing device, including
or bypassing the service provider computing device 160, to for
example, to provide an organic response to a query related to the
beach.
[0047] The data repository 145 can include one or more local or
distributed databases, and can include a database management
system. The data repository 145 can include computer data storage
or memory and can store one or more parameters 146, one or more
policies 147, content data 148, or templates 149 among other data.
The parameters 146, policies 147, and templates 149 can include
information such as rules about a voice based session between the
client computing device 102 and the data processing system 104 (or
the service provider computing device 160). The content data 148
can include content items for audio output or associated metadata,
as well as input audio messages that can be part of one or more
communication sessions with the client computing device 102.
[0048] The system 100 can optimize processing of action data
structures and content items in a voice activated data packet (or
other protocol) environment. For example, the data processing
system 104 can include or be part of a voice activated assistant
service, voice command device, intelligent personal assistant,
knowledge navigator, event planning, or another assistant program.
The data processing system 104 can provide one or more instances of
action data structures as audio output for display from the client
computing device 102 to accomplish tasks related to an input audio
signal. For example, the data processing system can communicate
with the service provider computing device 160 or other third party
computing devices to generate action data structures with
information about a beach, among other things. For example, an end
user can enter an input audio signal into the client computing
device 102 of: "OK, I would like to go to the beach this weekend"
and an action data structure can indicate the weekend weather
forecast for area beaches, such as "it will be sunny and 80 degrees
at the beach on Saturday, with high tide at 3 pm."
[0049] The action data structures can include a number of organic
or non-sponsored responses to the input audio signal. For example,
the action data structures can include a beach weather forecast or
directions to a beach. The action data structures in this example
include organic or non-sponsored content that is directly
responsive to the input audio signal. The content items responsive
to the input audio signal can include sponsored or non-organic
content, such as an offer to buy sunscreen from a convenience store
located near the beach. In this example, the organic action data
structure (beach forecast) is responsive to the input audio signal
(a query related to the beach), and the content item (a reminder or
offer for sunscreen) is also responsive to the same input audio
signal. The data processing system 104 can evaluate system 100
parameters (e.g., power usage, available displays, formats of
displays, memory requirements, bandwidth usage, power capacity or
time of input power (e.g., internal battery or external power
source such as a power source from a wall output) to provide the
action data structure and the content item to different candidate
interfaces on the same client computing device 102, or to different
candidate interfaces on different client computing devices 102.
[0050] The data processing system 104 can include an application,
script or program installed at the client computing device 102,
such as an app to communicate input audio signals (e.g., as data
packets via a packetized or other protocol based transmission) to
at least one interface 115 of the data processing system 104 and to
drive components of the client computing device 102 to render
output audio signals (e.g., for action data structures) or other
output signals (e.g., content items). The data processing system
104 can receive data packets or other signal that includes or
identifies an audio input signal. For example, the data processing
system 104 can execute or run the NLP component 110 to receive the
audio input signal.
[0051] The NLP component 110 can convert the audio input signal
into recognized text by comparing the input signal against a
stored, representative set of audio waveforms (e.g., in the data
repository 145) and choosing the closest matches. The
representative waveforms are generated across a large set of users,
and can be augmented with speech samples. After the audio signal is
converted into recognized text, the NLP component 110 can match the
text to words that are associated, for example, via training across
users or through manual specification, with actions that the data
processing system 104 can serve.
[0052] The audio input signal can be detected by the sensor 151
(e.g., a microphone) of the client computing device. Via the
transducer 152, the audio driver 153, or other components the
client computing device 102 can provide the audio input signal to
the data processing system 104 (e.g., via the network 106) where it
can be received (e.g., by the interface 115) and provided to the
NLP component 110 or stored in the data repository 145 as content
data 148.
[0053] The NLP component 110 can receive or otherwise obtain the
input audio signal. From the input audio signal, the NLP component
110 can identify at least one request or at least one trigger
keyword corresponding to the request. The request can indicate
intent or subject matter of the input audio signal. The trigger
keyword can indicate a type of action likely to be taken. For
example, the NLP component 110 can parse the input audio signal to
identify at least one request to go to the beach for the weekend.
The trigger keyword can include at least one word, phrase, root or
partial word, or derivative indicating an action to be taken. For
example, the trigger keyword "go" or "to go to" from the input
audio signal can indicate a need for transport or a trip away from
home. In this example, the input audio signal (or the identified
request) does not directly express an intent for transport, however
the trigger keyword indicates that transport is an ancillary action
to at least one other action that is indicated by the request.
[0054] The prediction component 120 (or other mechanism of the data
processing system 104) can generate, based on the request or the
trigger keyword, at least one action data structure associated with
the input audio signal. The action data structure can indicate
information related to subject matter of the input audio signal.
The action data structure can include one or more than one action,
such as organic responses to the input audio signal. For example,
the input audio signal "OK, I would like to go to the beach this
weekend" can include at least one request indicating an interest
for a beach weather forecast, surf report, or water temperature
information, and at least one trigger keyword, e.g., "go"
indicating travel to the beach, such as a need for items one may
want to bring to the beach, or a need for transportation to the
beach. The prediction component 120 can generate or identify
subject matter for at least one action data structure, an
indication of a request for a beach weather forecast, as well as
subject matter for a content item, such as an indication of a query
for sponsored content related to spending a day at a beach. From
the request or the trigger keyword the prediction component 120 (or
other system 100 component such as the NLP component 110 or the
direct action API 135) predicts, estimates, or otherwise determines
subject matter for action data structures or for content items.
From this subject matter, the direct action API 135 can generate at
least one action data structure and can communicate with at least
one content provider computing device 108 to obtain at least one
content item 110. The prediction component 120 can access the
parameters 146 or policies 147 in the data repository 145 to
determine or otherwise estimate requests for action data structures
or content items. For example, the parameters 146 or policies 147
could indicate requests for a beach weekend weather forecast action
or for content items related to beach visits, such as a content
item for sunscreen.
[0055] The content selector component 125 can obtain indications of
any of the interest in or request for the action data structure or
for the content item. For example, the prediction component 120 can
directly or indirectly (e.g., via the data repository 145) provide
an indication of the action data structure or content item to the
content selector component 125. The content selector component 125
can obtain this information from the data repository 145, where it
can be stored as part of the content data 148. The indication of
the action data structure can inform the content selector component
125 of a need for area beach information, such as a weather
forecast or products or services the end user may need for a trip
to the beach.
[0056] From the information received by the content selector
component 125, e.g., an indication of a forthcoming trip to the
beach, the content selector component 125 can identify at least one
content item. The content item can be responsive or related to the
subject matter of the input audio query. For example, the content
item can include data message identifying as tore near the beach
that has sunscreen, or offering a taxi ride to the beach. The
content selector component 125 can query the data repository 145 to
select or otherwise identify the content item, e.g., from the
content data 148. The content selector component 125 can also
select the content item from the content provider computing device
108. For example, responsive to a query received from the data
processing system 104, the content provider computing device 108
can provide a content item to the data processing system 104 (or
component thereof) for eventual output by the client computing
device 102 that originated the input audio signal, or for output to
the same end user by a different client computing device 102.
[0057] The audio signal generator component 130 can generate or
otherwise obtain an output signal that includes the content item
(as well as the action data structure) responsive to the input
audio signal. For example, the data processing system 104 can
execute the audio signal generator component 130 to generate or
create an output signal corresponding to the action data structure
or to the content item. The interface component 115 of the data
processing system 104 can provide or transmit one or more data
packets that include the output signal via the computer network 106
to any client computing device 102. The interface 115 can be
designed, configured, constructed, or operational to receive and
transmit information using, for example, data packets. The
interface 115 can receive and transmit information using one or
more protocols, such as a network protocol. The interface 115 can
include a hardware interface, software interface, wired interface,
or wireless interface. The interface 115 can facilitate translating
or formatting data from one format to another format. For example,
the interface 115 can include an application programming interface
that includes definitions for communicating between various
components, such as software components of the system 100.
[0058] The data processing system 104 can provide the output signal
including the action data structure from the data repository 145 or
from the audio signal generator component 130 to the client
computing device 102. The data processing system 104 can provide
the output signal including the content item from the data
repository 145 or from the audio signal generator component 130 to
the same or to a different client computing device 102.
[0059] The data processing system 104 can also instruct, via data
packet transmissions, the content provider computing device 108 or
the service provider computing device 160 to provide the output
signal (e.g., corresponding to the action data structure or to the
content item) to the client computing device 102. The output signal
can be obtained, generated, transformed to or transmitted as one or
more data packets (or other communications protocol) from the data
processing system 104 (or other computing device) to the client
computing device 102.
[0060] The content selector component 125 can select the content
item or the action data structure for the as part of a real-time
content selection process. For example, the action data structure
can be provided to the client computing device 102 for transmission
as audio output by an interface of the client computing device 102
in a conversational manner in direct response to the input audio
signal. The real-time content selection process to identify the
action data structure and provide the content item to the client
computing device 102 can occur within one minute or less from the
time of the input audio signal and be considered real-time. The
data processing system 104 can also identify and provide the
content item to at least one interface of the client computing
device 102 that originated the input audio signal, or to a
different client computing device 102.
[0061] The action data structure (or the content item), For
example, obtained or generated by the audio signal generator
component 130 transmitted via the interface 115 and the computer
network 106 to the client computing device 102, can cause the
client computing device 102 to execute the audio driver 153 to
drive the speaker 154 to generate an acoustic wave corresponding to
the action data structure or to the content item. The acoustic wave
can include words of or corresponding to the action data structure
or content item.
[0062] The acoustic wave representing the action data structure can
be output from the client computing device 102 separately from the
content item. For example, the acoustic wave can include the audio
output of "Today it will be sunny and 80 degrees at the beach." In
this example, the data processing system 104 obtains the input
audio signal of, for example, "OK, I would like to go to the beach
this weekend." From this information, the NLP component 110
identifies at least one request or at least one trigger keyword,
and the prediction component 120 uses the request(s) or trigger
keyword(s) to identify a request for an action data structure or
for a content item. The content selector component 125 (or other
component) can identify, select, or generate a content item for,
e.g., sunscreen available near the beach. The direct action API 135
(or other component) can identify, select, or generate an action
data structure for, e.g., the weekend beach forecast. The data
processing system 104 or component thereof such as the audio signal
generator component 130 can provide the action data structure for
output by an interface of the client computing device 102. For
example, the acoustic wave corresponding to the action data
structure can be output from the client computing device 102. The
data processing system 104 can provide the content item for output
by a different interface of the same client computing device 102 or
by an interface of a different client computing device 102.
[0063] The packet based data transmission of the action data
structure by data processing system 104 to the client computing
device 102 can include a direct or real-time response to the input
audio signal of "OK, I would like to go to the beach this weekend"
so that the packet based data transmissions via the computer
network 106 that are part of a communication session between the
data processing system 104 and the client computing device 102 with
the flow and feel of a real-time person to person conversation.
This packet based data transmission communication session can also
include the content provider computing device 108 or the service
provider computing device 160.
[0064] The content selector component 125 can select the content
item or action data structure based on at least one request or at
least one trigger keyword of the input audio signal. For example,
the requests of the input audio signal "OK, I would like to go to
the beach this weekend" can indicate subject matter of the beach,
travel to the beach, or items to facilitate a trip to the beach.
The NLP component 110 or the prediction component 120 (or other
data processing system 104 components executing as part of the
direct action API 135) can identify the trigger keyword "go" "go
to" or "to go to" and can determine a transportation request to the
beach based at least in part on the trigger keyword. The NLP
component 110 (or other system 100 component) can also determine a
solicitation for content items related to beach activity, such as
for sunscreen or beach umbrellas. Thus, the data processing system
104 can infer actions from the input audio signal that are
secondary requests (e.g., a request for sunscreen) that are not the
primary request or subject of the input audio signal (information
about the beach this weekend).
[0065] The action data structures and content items can correspond
to subject matter of the input audio signal. The direct action API
135 can execute programs or scripts, for example, from the NLP
component 110, the prediction component 120, or the content
selector component 125 to identify action data structures or
content items for one or more of these actions. The direct action
API 135 can execute a specified action to satisfy the end user's
intention, as determined by the data processing system 104.
Depending on the action specified in its inputs, the direct action
API 135 can execute code or a dialog script that identifies the
parameters required to fulfill a user request. Such code can lookup
additional information, e.g., in the data repository 145, such as
the name of a home automation service, or it can provide audio
output for rendering at the client computing device 102 to ask the
end user questions such as the intended destination of a requested
taxi. The direct action API 135 can determine necessary parameters
and can package the information into an action data structure,
which can then be sent to another component such as the content
selector component 125 or to the service provider computing device
160 to be fulfilled.
[0066] The direct action API 135 of the data processing system 104
can generate, based on the request or the trigger keyword, the
action data structures. The action data structures can be generated
responsive to the subject matter of the input audio signal. The
action data structures can be included in the messages that are
transmitted to or received by the service provider computing device
160. Based on the audio input signal parsed by the NLP component
110, the direct action API 135 can determine to which, if any, of a
plurality of service provider computing devices 160 the message
should be sent. For example, if an input audio signal includes "OK,
I would like to go to the beach this weekend," the NLP component
110 can parse the input audio signal to identify requests or
trigger keywords such as the trigger keyword word "to go to" as an
indication of a need for a taxi. The direct action API 135 can
package the request into an action data structure for transmission
as a message to a service provider computing device 160 of a taxi
service. The message can also be passed to the content selector
component 125. The action data structure can include information
for completing the request. In this example, the information can
include a pick up location (e.g., home) and a destination location
(e.g., a beach). The direct action API 135 can retrieve a template
149 from the data repository 145 to determine which fields to
include in the action data structure. The direct action API 135 can
retrieve content from the data repository 145 to obtain information
for the fields of the data structure. The direct action API 135 can
populate the fields from the template with that information to
generate the data structure. The direct action API 135 can also
populate the fields with data from the input audio signal. The
templates 149 can be standardized for categories of service
providers or can be standardized for specific service providers.
For example, ride sharing service providers can use the following
standardized template 149 to create the data structure:
{client.sub.deviceidentifier; authentication.sub.credentials;
pick.sub.uplocation; destination.sub.location; no.sub.passengers;
service.sub.level}.
[0067] The content selector component 125 can identify, select, or
obtain multiple content items resulting from a multiple content
selection processes. The content selection processes can be
real-time, e.g., part of the same conversation, communication
session, or series of communications sessions between the data
processing system 104 and the client computing device 102 that
involve common subject matter. The conversation can include
asynchronous communications separated from one another by a period
of hours or days, for example. The conversation or communication
session can last for a time period from receipt of the first input
audio signal until an estimated or known conclusion of a final
action related to the first input audio signal, or receipt by the
data processing system 104 of an indication of a termination or
expiration of the conversation. For example, the data processing
system 104 can determine that a conversation related to a weekend
beach trip begins at the time or receipt of the input audio signal
and expires or terminates at the end of the weekend, e.g., Sunday
night or Monday morning. The data processing system 104 that
provides action data structures or content items for rendering by
one or more interfaces of the client computing device 102 or of
another client computing device 102 during the active time period
of the conversation (e.g., from receipt of the input audio signal
until a determined expiration time) can be considered to be
operating in real-time. In this example, the content selection
processes and rendering of the content items and action data
structures occurs in real time.
[0068] The interface management component 140 can poll, determine,
identify, or select interfaces for rendering of the action data
structures and of the content items related to the input audio
signal. For example, the interface management component 140 can
identify one or more candidate interfaces of client computing
devices 102 associated with an end user that entered the input
audio signal (e.g., "What is the weather at the beach today?") into
one of the client computing devices 102 via an audio interface. The
interfaces can include hardware such as sensor 151 (e.g., a
microphone), speaker 154, or a screen size of a computing device,
alone or combined with scripts or programs (e.g., the audio driver
153) as well as apps, computer programs, online documents (e.g.,
webpage) interfaces and combinations thereof.
[0069] The interfaces can include social media accounts, text
message applications, or email accounts associated with an end user
of the client computing device 102 that originated the input audio
signal. Interfaces can include the audio output of a smartphone, or
an app based messaging device installed on the smartphone, or on a
wearable computing device, among other client computing devices
102. The interfaces can also include display screen parameters
(e.g., size, resolution), audio parameters, mobile device
parameters, (e.g., processing power, battery life, existence of
installed apps or programs, or sensor 151 or speaker 154
capabilities), content slots on online documents for text, image,
or video renderings of content items, chat applications, laptops
parameters, smartwatch or other wearable device parameters (e.g.,
indications of their display or processing capabilities), or
virtual reality headset parameters.
[0070] The interface management component 140 can poll a plurality
of interfaces to identify candidate interfaces. Candidate
interfaces include interfaces having the capability to render a
response to the input audio signal, (e.g., the action data
structure as an audio output, or the content item that can be
output in various formats including non-audio formats). The
interface management component 140 can determine parameters or
other capabilities of interfaces to determine that they are (or are
not) candidate interfaces. For example, the interface management
component 140 can determine, based on parameters 146 of the content
item or of a first client computing device 102 (e.g., a smartwatch
wearable device), that the smartwatch includes an available visual
interface of sufficient size or resolution to render the content
item. The interface management component 140 can also determine
that the client computing device 102 that originated the input
audio signal has a speaker 154 hardware and installed program e.g.,
an audio driver or other script to render the action data
structure.
[0071] The interface management component 140 can determine
utilization values for candidate interfaces. The utilization values
can indicate that a candidate interface can (or cannot) render the
action data structures or the content items provided in response to
input audio signals. The utilization values can include parameters
146 obtained from the data repository 145 or other parameters
obtained from the client computing device 102, such as bandwidth or
processing utilizations or requirements, processing power, power
requirements, battery status, memory utilization or capabilities,
or other interface parameters that indicate the available of an
interface to render action data structures or content items. The
battery status can indicate a type of power source (e.g., internal
battery or external power source such as via an output), a charging
status (e.g., currently charging or not), or an amount of remaining
battery power. The interface management component 140 can select
interfaces based on the battery status or charging status.
[0072] The interface management component 140 can order the
candidate interfaces in a hierarchy or ranking based on the
utilization values. For example, different utilization values
(e.g., processing requirements, display screen size, accessibility
to the end user) can be given different weights. The interface
management component 140 can rank one or more of the utilization
values of the candidate interfaces based on their weights to
determine an optimal corresponding candidate interface for
rendering of the content item (or action data structure). Based on
this hierarchy, the interface management component 140 can select
the highest ranked interface for rendering of the content item.
[0073] Based on utilization values for candidate interfaces, the
interface management component 140 can select at least one
candidate interface as a selected interface for the content item.
The selected interface for the content item can be the same
interface from which the input audio signal was received (e.g., an
audio interface of the client computing device 102) or a different
interface (e.g., a text message based app of the same client
computing device 102, or an email account accessible from the same
client computing device 102.
[0074] The interface management component 140 can select an
interface for the content item that is an interface of a different
client computing device 102 than the device that originated the
input audio signal. For example, the data processing system 104 can
receive the input audio signal from a first client computing device
102 (e.g., a smartphone), and can select an interface such as a
display of a smartwatch (or any other client computing device for
rendering of the content item. The multiple client computing
devices 102 can all be associated with the same end user. The data
processing system 104 can determine that multiple client computing
devices 102 are associated with the same end user based on
information received with consent from the end user such as user
access to a common social media or email account across multiple
client computing devices 102.
[0075] The interface management component 140 can also determine
that an interface is unavailable. For example, the interface
management component 140 can poll interfaces and determine that a
battery status of a client computing device 102 associated with the
interface is low, or below a threshold level such as 10%. Or the
interface management component 140 can determine that the client
computing device 102 associated with the interface lacks sufficient
display screen size or processing power to render the content item,
or that the processor utilization rate is too high, as the client
computing device is currently executing another application, For
example, to stream content via the network 106. In these and other
examples the interface management component 140 can determine that
the interface is unavailable and can eliminate the interface as a
candidate for rendering the content item or the action data
structure.
[0076] Thus, the interface management component 140 can determine
that a candidate interface accessible by the first client computing
device 102 is linked to an account of an end user, and that a
second candidate interface accessible by a second client computing
device 102 is also linked to the same account. For example, both
client computing devices 102 may have access to the same social
media account, e.g., via installation of an app or script at each
client computing device 102. The interface management component 140
can also determine that multiple interfaces correspond to the same
account, and can provide multiple, different content items to the
multiple interfaces corresponding to the common account. For
example, the data processing system 104 can determine, with end
user consent, that an end user has accessed an account from
different client computing devices 102. These multiple interfaces
can be separate instances of the same interface (e.g., the same app
installed on different client computing devices 102) or different
interfaces such as different apps for different social media
accounts that are both linked to a common email address account,
accessible from multiple client computing devices 102.
[0077] The interface management component 140 can also determine or
estimate distances between client computing devices 102 associated
with candidate interfaces. For example, the data processing system
104 can obtain, with user consent, an indication that the input
audio signal originated from a smartphone or virtual reality
headset computing device 102, and that the end user is associated
with an active smartwatch client computing device 102. From this
information, the interface management component can determine that
the smartwatch is active, e.g., being worn by the end user when the
end user enters the input audio signal into the smartphone, so that
the two client computing devices 102 are within a threshold
distance of one another. In another example, the data processing
system 104 can determine, with end user consent, the location of a
smartphone that is the source of an input audio signal, and can
also determine that a laptop account associated with the end user
is currently active. For example, the laptop can be signed into a
social media account indicating that the user is currently active
on the laptop. In this example, the data processing system 104 can
determine that the end user is within a threshold distance of the
smartphone and of the laptop, so that the laptop can be an
appropriate choice for rendering of the content item via a
candidate interface.
[0078] The interface management component 140 can select the
interface for the content item based on at least one utilization
value indicating that the selected interface is the most efficient
for the content item. For example, from among candidate interfaces,
the interface to render the content item at the smartwatch uses the
least bandwidth due as the content item is smaller and can be
transmitted with fewer resources. Or the interface management
component 140 can determine that the candidate interface selected
for rendering of the content item is currently charging (e.g.,
plugged in) so that rendering of the content item by the interface
will not drain battery power of the corresponding client computing
device 102. In another example, the interface management component
140 can select a candidate interface that is currently performing
fewer processing operations than another, unselected interface of
for example, a different client computing device 102 that is
currently streaming video content from the network 106 and
therefore less available to render the content item without
delay.
[0079] The interface management component 140 (or other data
processing system 104 component) can convert the content item for
delivery in a modality compatible with the candidate interface. For
example, if the candidate interface is a display of a smartwatch,
smartphone, or tablet computing device, the interface management
component 140 can size the content item for appropriate visual
display given the dimensions of the display screen associated with
the interface. The interface management component 140 can also
convert the content item to a packet or other protocol based
format, including proprietary or industry standard format for
transmission to the client computing device 102 associated with the
selected interface. The interface selected by the interface
management component 140 for the content item can include an
interface accessible from multiple client computing devices 102 by
the end user. For example, the interface can be or include a social
media account that the end user can access via the client computing
device 102 that originated the input audio signal (e.g., a
smartphone) as well as other client computing devices such as
tabled or desktop computers or other mobile computing devices.
[0080] The interface management component 140 can also select at
least one candidate interface for the action data structure. This
interface can be the same interface from which the input audio
signal was obtained, e.g., a voice activated assistant service
executed at a client computing device 102. This can be the same
interface or a different interface than the interface management
component 140 selects for the content item. The interface
management component 140 (or other data processing system 104
components) can provide the action data structure to the same
client computing device 102 that originated the input audio signal
for rendering as audio output as part of the assistant service. The
interface management component 140 can also transmit or otherwise
provide the content item to the selected interface for the content
item, in any converted modality appropriate for rendering by the
selected interface.
[0081] Thus, the interface management component 140 can provide the
action data structure as audio output for rendering by an interface
of the client computing device 102 responsive to the input audio
signal received by the same client computing device 102. The
interface management component 140 can also provide the content
item for rendering by a different interface of the same client
computing device 102 or of a different client computing device 102
associated with the same end user. For example, the action data
structure, e.g., "it will be sunny and 80 degrees at the beach on
Saturday" can be provided for audio rendering by the client
computing device as part of an assistant program interface
executing in part at the client computing device 102, and the
content item e.g., a text, audio, or combination content item
indicating that "sunscreen is available from the convenience store
near the beach" can be provided for rendering by an interface of
the same or a different computing device 102, such as an email or
text message accessible by the same or a different client computing
device 102 associated with the end user.
[0082] Separating the content item from the action data structure
and sending the content item as, for example, a text message rather
than an audio message can result in reduced processing power for
the client computing device 102 that accesses the content item
since, for example, text message data transmissions are less
computationally intensive than audio message data transmissions.
This separation can also reduce power usage, memory storage, or
transmission bandwidth used to render the content item. This
results in increased processing, power, and bandwidth efficiencies
of the system 100 and devices such as the client computing devices
102 and the data processing system 104. This increases the
efficiency of the computing devices that process these
transactions, and increases the speed with which the content items
can be rendered. The data processing system 104 can process
thousands, tens of thousands or more input audio signals
simultaneously so the bandwidth, power, and processing savings can
be significant and not merely incremental or incidental.
[0083] The interface management component 140 can provide or
deliver the content item to the same client computing device 102
(or a different device) as the action data structure subsequent to
delivery of the action data structure to the client computing
device 102. For example, the content item can be provided for
rendering via the selected interface upon conclusion of audio
output rendering of the action data structure. The interface
management component 140 can also provide the content item to the
selected interface concurrent with the provision of the action data
structure to the client computing device 102. The interface
management component 140 can provide the content item for delivery
via the selected interface within a pre-determined time period from
receipt of the input audio signal by the NLP component 110. The
time period, for example, can be any time during an active length
of the conversation of session. For example, if the input audio
signal is "I would like to go to the beach this weekend" the
pre-determined time period can be any time from receipt of the
input audio signal through the end of the weekend, e.g., the active
period of the conversation. The pre-determined time period can also
be a time triggered from rendering of the action data structure as
audio output by the client computing device 102, such as within 5
minutes, one hour or one day of this rendering.
[0084] The interface management component 140 can provide the
action data structure to the client computing device 102 with an
indication of the existence of the content item. For example, the
data processing system 104 can provide the action data structure
that renders at the client computing device 102 to provide the
audio output "it will be sunny and 80 degrees at the beach on
Saturday, check your email for more information." The phrase "check
your email for more information" can indicate the existence of a
content item, e.g., for sunscreen, provided by the data processing
system 104 to an interface (e.g., email). In this example,
sponsored content can be provided as content items to the email (or
other) interface and organic content such as the weather can be
provided as the action data structure for audio output.
[0085] The data processing system 104 can also provide the action
data structure with a prompt that queries the user to determine
user interest in obtaining the content item. For example, the
action data structure can indicate "it will be sunny and 80 degrees
at the beach on Saturday, would you like to hear about some
services to assist with your trip?" The data processing system 104
can receive another audio input signal from the client computing
device 102 in response to the prompt "would you like to hear about
some services to assist with your trip?" such as "sure". The NLP
component 110 can parse this response, e.g., "sure" and interpret
it as authorization for audio rendering of the content item by the
client computing device 102. In response, the data processing
system 104 can provide the content item for audio rendering by the
same client computing device 102 from which the response "sure"
originated.
[0086] The data processing system 104 can delay transmission of the
content item associated with the action data structure to optimize
processing utilization. For example, the data processing system 104
provide the action data structure for rendering as audio output by
the client computing device in real-time responsive to receipt of
the input audio signal, e.g., in a conversational manner, and can
delay content item transmission until an off-peak or non-peak
period of data center usage, which results in more efficient
utilization of the data center by reducing peak bandwidth usage,
heat output or cooling requirements. The data processing system 104
can also initiate a conversion or other activity associated with
the content item, such as ordering a car service responsive to a
response to the action data structure or to the content item, based
on data center utilization rates or bandwidth metrics or
requirements of the network 106 or of a data center that includes
the data processing system 104.
[0087] Based on a response to a content item or to the action data
structure for a subsequent action, such as a click on the content
item rendered via the selected interface, the data processing
system 104 can identify a conversion, or initiate a conversion or
action. Processors of the data processing system 104 can invoke the
direct action API 135 to execute scripts that facilitate the
conversion action, such as to order a car from a car share service
to take the end user to or from the beach. The direct action API
135 can obtain content data 148 (or parameters 146 or policies 147)
from the data repository 145, as well as data received with end
user consent from the client computing device 102 to determine
location, time, user accounts, logistical or other information in
order to reserve a car from the car share service. Using the direct
action API 135, the data processing system 104 can also communicate
with the service provider computing device 160 to complete the
conversion by in this example making the car share pick up
reservation.
[0088] FIG. 1C depicts a flow diagram 200 for multi-modal
transmission of packetized data in a voice activated computer
network environment. The data processing system 104 can receive the
input audio signal 205, e.g., "OK, I would like to go to the beach
this weekend." In response, the data processing system generates at
least one action data structure 211 and at least one content item
215. The action data structure 205 can include organic or
non-sponsored content, such as a response for audio rendering
stating "It will be sunny and 80 degrees at the beach this weekend"
or "high tide is at 3 pm." The data processing system 104 can
provide the action data structure 211 to the same client computing
device 102 that originated the input audio signal 205, for
rendering by a candidate interface of the client computing device
102, e.g., as output in a real time or conversational manner as
part of a digital or conversational assistant platform.
[0089] The data processing system 104 can select the candidate
interface 220 as a selected interface for the content item 215, and
can provide the content item 215 to the selected interface 220. The
content item 215 can also include a data structure, converted to
the appropriate modality by the data processing system 104 for
rendering by the selected interface 220. The content item 215 can
include sponsored content, such as an offer to rent a beach chair
for the day, or for sunscreen. The selected interface 220 can be
part of or executed by the same client computing device 102 or by a
different device accessible by the end user of the client computing
device 102. Transmission of the action data structure 211 and the
content item 215 can occur at the same time or subsequent to one
another. The action data structure 211 can include an indicator
that the content item 215 is being or will be transmitted
separately via a different modality or format to the selected
interface 220, alerting the end user to the existence of the
content item 215.
[0090] The action data structure 211 and the content item 215 can
be provided separately for rendering to the end user. By separating
the sponsored content (content item 215) from the organic response
(action data structure 211) audio or other alerts indicating that
the content item 215 is sponsored do not need to be provided with
the action data structure 211. This can reduce bandwidth
requirements associated with transmission of the action data
structure 211 via the network 106 and can simplify rendering of the
action data structure 211. For example, without audio disclaimer or
warning messages.
[0091] The data processing system 104 can receive a response audio
signal 225. The response audio signal 225 can include an audio
signal such as, "great, please book me a hotel on the beach this
weekend." Receipt by the data processing system 104 of the response
audio signal 225 can cause the data processing system to invoke the
direct action API 135 to execute a conversion to, for example, book
a hotel room on the beach. The direct action API 135 can also
communicate with at least one service provider computing device 160
to provide information to the service provider computing device 160
so that the service provider computing device 160 can complete or
confirm the booking process.
[0092] FIG. 2 is an example of an illustration of a block diagram
of a system 100 for serving digital components for a minimum number
of exposures in accordance with a described implementation.
[0093] In a brief overview, system 100 includes document 202, data
processing system 104, and service provider module 206. Generally,
system 100 allows service providers to set a minimum number of
exposures over an interval of time, and a per-user maximum
aggregate bid value for meeting the minimum number of exposures
within the interval of time.
[0094] Document 202 may include any machine-readable content, which
may include text, graphics, images, videos, multimedia graphics,
etc. Document 202 may be encoded in a markup language, e.g.,
Hypertext Markup Language (HTML), e.g., a web page rendered in
JavaScript or in any other machine readable or executable format.
Document 202 may include a hyperlink to another document.
[0095] Document 202 may receive device identifier 203 when document
202 is rendered to client computing device 102. Device identifier
203 may be stored by client computing device 102. Device identifier
203 may be included in a user record, e.g., a user profile. Device
identifier 203 may associate the information in the user record to
a particular user or client computing device 102. A user may opt in
or out of allowing data processing system 104 or other content
source to identify and store information about the user and/or
about devices operated by the user. For example, the user may opt
in to receiving digital components from data processing system 104
that may be more relevant to her. In one implementation, the user
may be represented as a randomized device identifier (e.g., a
cookie, a device serial number, etc.) that contains no
personally-identifiable information about the user. For example,
information relating to the user's name, demographics, etc., may
not be used by a digital component server unless the user opts in
to providing such information. Thus, the user may have control over
how information is collected about him or her and used by a digital
component server or other content source.
[0096] In some implementations, device identifier 203 is associated
with a particular instance of a client application (e.g., running
on client computing device 102). In some implementations, device
identifier 203 is associated with a user (e.g., when the user logs
in with a username and password). Some information that may be
associated with the user may include events, such as one or more
queries, one or more clicks, browser history data (e.g., the URLs
visited, the number of URLs viewed, URL visit durations, etc.),
etc. Events may also include digital component metrics, such as
impressions, click through rate, etc. for each user. For example,
device identifier 203 may include a time stamp associated with a
particular event. Events may also include exposure data 208, e.g.,
how many times a user is exposed to a particular ad, a campaign,
etc. In some implementations, exposure data 208 may include the
number of exposures associated with device identifier 203, a time
stamp of the exposures (when), and how the exposures occurred
(e.g., placement of the digital component, interaction with the
digital component, etc.).
[0097] A content network may select content to be provided with a
webpage based on device identifier 203 for a user visiting document
202. For example, a user may opt in to receiving relevant digital
components from a digital component server. Rather than selecting a
digital component to be provided on document 202 based on the
content of document 202 itself or on other factors, data processing
system 104 may take into account device identifier 203 provided as
part of a content request. In one example, a user may visit a
number of webpages devoted to reviews of golf clubs and later visit
a webpage to check stock quotes. Based on the user's visits to the
golf-related webpages, the user may be determined to be interested
in receiving digital components for golf clubs. When the user later
visits the webpage to check stock quotes, an online retailer of
golf equipment may seek to include a digital component on the
webpage for that particular user, even though the financial webpage
is unrelated to golf.
[0098] If content is selected based in part on a device identifier
for a user that opts in to receiving more relevant content, a
content provider may specify that certain content is to be provided
to a set of device identifiers. For example, a service provider may
identify a set of device identifiers associated with visiting the
service provider's website and making a purchase. Such users may
later wish to know if the service provider is running a sale. In
some cases, a digital component network may identify users on
behalf of the service provider that may be interested in receiving
digital components from the service provider. For example, service
providers may specify a number of topic categories for their
digital components and the digital component network may match
users' interests to the categories, to provide relevant digital
components to the users.
[0099] Device identifier 203 may be received by data processing
system 104. Data processing system 104 may retrieve exposure data
208. For example, exposure data 208 may include the number of
exposures to device identifier 203. Exposure data 208 may also
include how recent the exposures were to device identifier 203 or
when the exposures occurred.
[0100] Data processing system 104 may receive digital component
metrics and selection criteria 206. For example, data processing
system 104 may receive the total number of different viewers
exposed to the digital component (at least once, twice, etc.)
during an interval of time, which may be determined by the service
provider, publisher, etc. Selection criteria 206 may include
demographics, placement, geo-location, etc., which may be
determined by the service provider, publisher, etc. Selection
criteria 206 may also include budgetary criteria. For example, the
service provider may provide a per-user maximum aggregate bid value
210 for meeting the minimum number of exposures. In some
implementations, the minimum number of exposures may have to occur
within an interval of time. In another implementation, data
processing system 104 may store device identifier 203 and exposure
data 208.
[0101] In some implementations, data processing system 104 stores
selection criteria 206. In another implementation, data processing
system 104 determines the probability 212 that device identifier
203 will receive the minimum number of exposures within the
interval of time and within the maximum aggregate bid value 210,
e.g., exposure data 208. Given the probability 212, digital
component server may adjust bidding data 214 with the budgetary
criteria (e.g., the per-user maximum aggregate bid value).
[0102] FIG. 3 is an illustration 300 of a user interface that
allows the service provider to determine selection criteria. In the
example, the service provider may determine the following settings
310, a minimum number of exposures at input field 302, a start date
at input field 304, an end date at input field 306, a maximum bid
per user, and a maximum bid for exposure, or a maximum CPM (cost
per mille) at input field 308. Other variations of the settings may
be implemented. Once these settings are entered, the system may
determine the estimated number of expected unique users at output
field 320.
[0103] For example, the service provider may determine that a user
needs to view their digital component message three times within a
week for the user to be aware of the digital component message,
thereby entering three at input field 302, and a start date at
input field 304, and an end date at input field 306.
[0104] At input field 308, the service provider may determine a
maximum aggregate bid value 210 of $12 per user as an appropriate
maximum amount to pay for exposing the user to the digital
component message for the minimum of three times within one week.
The service provider may also enter a maximum bid per exposure or
CPM.
[0105] At output field 320, the system may automatically estimate
the number of expected unique users that the digital component will
be exposed to. The service provider can then alter input fields
302-308 to change output field 310.
[0106] Data processing system 104 receives selection criteria 206
that may include exposure data 208 of a minimum of three exposures
per user within one week. Data processing system 104 may also
receive the budgetary criteria that include the maximum aggregate
bid value per user of $12.
[0107] In the example, data processing system 104 may determine the
probability that a user is likely to meet the minimum number of
three exposures within one week given selection criteria 206. Data
processing system 104 may provide bidding data 214 for each
exposure based on the determined probability 212 and the maximum
aggregate bid value of $12 per user. If and when the auction is
won, the digital component 216 may be provided, while updating
device identifier 203 and/or data processing system 104.
[0108] FIG. 4 is an illustration 400 of a system for updating the
device identifier in accordance with a described implementation.
Illustration 400 may include client computing device 102 including
device identifier 203, data processing system 104, count module 402
and data repository 145.
[0109] Client computing device 102 may receive a rendered web page
along with a digital component from data processing system 104. The
digital component may be selected by the service provider as a
digital component having a goal for a minimum number of exposures
within an interval of time.
[0110] Count module 402 receives information from data processing
system 104 that the digital component has been provided to client
computing device 102. Count module 402 may update the number of
exposures. Count module 402 may store the number of exposures as
exposure data in data repository 145.
[0111] In some implementations, data repository 145 may receive
exposure data in order to determine which digital component to
generate and provide to data processing system 104. Data repository
145 may include digital components that are tagged with exposure
data or data repository 145 may tag the digital components with the
exposure data. Data repository 145 may provide the digital
components tagged with exposure data to client computing device 102
or to data processing system 104 to be displayed on a web page.
[0112] In some implementations, client computing device 102
provides exposure data to data processing system 104 after
receiving a rendered document 202 from data processing system 104.
In other implementations, Client computing device 102 may provide
the exposure data to data repository 145.
[0113] FIG. 5 is an example of a flow diagram of a method 500 to
provide a digital component with a minimum number of exposures.
Example method 500 may be implemented by various combinations of
systems. Example method 500 may be performed online or offline.
[0114] Example method may begin at ACT 502, selection criteria to
specify the device identifier that meets the selection criteria is
received. For example, the selection criteria may define one or
more characteristics of the users to which the digital component is
directed. If a device identifier has one or more of the defined
characteristics, then the device identifier meets the selection
criteria. If the device identifier does not include one or more (or
at least a threshold number) of the characteristics, then the
digital component may not be provided to the device identifier. In
some implementations, the selection criteria may include budgetary
criteria, e.g., one or more bids.
[0115] At ACT 504, a minimum number of exposures to the digital
component and an interval of time for the minimum number of
exposures to occur is received. In some implementations, the
minimum number of exposures is stored in a memory. A maximum
aggregate bid value to be paid for each device identifier that is
exposed to the digital component for a minimum number of exposures
may also be received. In some implementations, the minimum number
of exposures and the interval of time includes a frequency, e.g.,
how many times the digital component is exposed within a set period
of time. In some implementations, the interval of time may include
a length of time the digital component is exposed, e.g., 1 week. In
other implementations, the interval of time may include a time of
day when the digital component is exposed.
[0116] At ACT 506, a probability that the device identifier reaches
the number of exposures within the interval of time and the maximum
aggregate bid value is determined. Probability may be determined
using a number of methods including, but not limited to,
distributed gradient descent and logistic regression.
[0117] If there is sufficient historical data for a user, then the
application of the desired interval of time and the desired
selection criteria are applied to produce a prediction. In this
implementation, statistical methods may not be needed. Either the
prediction will indicate that the user will meet the minimum number
of exposures in the interval of time or not.
[0118] If there is not sufficient historical data for a user, then
the system may determine by an estimation or a guess whether the
user will meet the minimum number of exposures within the interval
of time. In an example, the system may receive the historical data
that it does have for the user to compare the data to a population
of similar users that have sufficient historical data, e.g., any
correlated or detectable data may be used. The population of
similar users may produce a probability of meeting the minimum
number of exposures within the interval of time for the desired
selection criteria. This probability is then applied to the newly
observed user, e.g., if seventy percent of the similar population
would meet the minimum number of exposures, then the 0.7
probability is applied to the newly observed user.
[0119] At ACT 508, a bid for each exposure for the device
identifier based on the determined probability and the maximum
aggregate bid value is selected. When selection criteria are met,
then the probability is determined at ACT 510, which may produce a
weight used to adjust a bid. The higher the probability, then the
higher the bid, with a maximum combination of minimum exposures not
exceeding the maximum aggregate bid value.
[0120] In some implementations, the probability may be conditional
and adjusted based on the number of exposures. For example, a user
that is one exposure away from meeting the minimum number of
exposures may receive a higher bid than a user that is three
exposures away, provided all other criteria is equal. The system
may also determine a different probability for each user. A weight
may also be determined to select a bid.
[0121] At ACT 512, a bid is selected for each exposure for the
device identifier based on the determined probability and the
maximum aggregate bid value. The weight is the mechanism that can
adjust a bid to favor impressions that are more likely to meet the
goal minimum number of exposures in the interval of time. In some
implementations, the probability may be used as the weight. In this
implementation, however, campaign constraints may limit how low or
high the weight can be set.
[0122] The weight used to adjust a bid may be determined by
historical impression data, for each device identifier, while also
applying the selection criteria and the interval of time. If there
are a sufficient number of impressions to meet the minimum number
of exposures, then the bidding weight may be applied. If there is
not a sufficient number of impressions, then no bidding weight may
be applied. The probability is used to change the bid when the user
is close to meeting the minimum number of exposures. In other
implementations, the probability may not be used when the user is
far from meeting the minimum number of exposures.
[0123] In another example, there may not be enough information to
determine the probability, because the user is new or there is not
enough historical impression data. In these cases, the probability
may be determined based on whether similar device identifiers meet
the minimum number of exposures within the interval of time.
Similar users may be selected based on regression analysis, where
user characteristics, such as, but not limited to, browser,
operating system, browser history, interests, etc., may determine
whether the user will meet the minimum number of exposures. Then, a
user model may be constructed along with the probability. The
probability from the model may be used to set the bidding weight to
bias exposures to users most likely to meet the minimum number of
exposures within the interval of time.
[0124] At ACT 514, a digital component is served on selection of
the bid. In some implementations, serving may include providing
display data, which may be indicative of the digital component. The
digital component server may provide the display data to the client
device. The digital component server may be configured to cause the
client to display the digital component. In some implementations,
the display data may cause the digital component to be displayed.
In other implementations, the display data may include the digital
component itself. In yet another implementation, the display data
may include a selection of a digital component present on the
client device, e.g., the digital component server alerts the client
device that there is a selected digital component. The display data
may be provided to an interface, e.g., a graphical user interface,
a command line interface, etc. At ACT 516, the count is updated
representing the number of exposures of device identifier to the
digital component, as shown in FIG. 4.
[0125] In an alternative implementation, the total number of
different users exposed to the digital component message during a
given period and how many times they are exposed to the digital
component message may be predicted for a content campaign, e.g.,
using gross rating points or target rating points, which equate to
how many times the message aired times the number of users that
were exposed to the digital component message. The bid may be
adjusted so that the prediction aligns with the minimum number of
exposures per user for the total number of users exposed.
[0126] FIG. 6 illustrates a block diagram of an example method 600
to transmit digital components. The method 600 can include
receiving an audio-based request (ACT 602). The method 600 can
include receiving selection criteria (ACT 604). The method 600 can
include identifying a plurality of digital components (ACT 606).
The method 600 can include determining a count (ACT 608). The
method 600 can include receiving a target number (ACT 610). The
method 600 can include determining a probability (ACT 612). The
method 600 can include selecting a candidate digital component (ACT
614) and transmitting the candidate digital component (ACT
616).
[0127] The method 600 can include receiving an audio-based request
(ACT 602). The data processing system can receive the request from
a computing device. The audio-based request can include a device
identifier that is associated with the computing device. The
audio-based request can be detected at the computing device. For
example, the audio-based request can be detected at a microphone
positioned at or the computing device. In some implementations, the
request can be a text-based, image-based, or video-based requests
that can be input into the computing device with a physical or
digital keyboard or a camera. The request can be included in an
input audio signal.
[0128] A NLP component 110, that is executed by the data processing
system 104, can receive the audio-based request. The NLP component
110 can receive the request via an interface of the data processing
system 104. The NLP component 110 can receive the request as a
plurality of data packets that can include the audio-based input
signal. The data packets can be received at the data processing
system, via a network, as packet or other protocol based data
transmissions. The request can be encoded as an input audio signal
by the computing device that transmits the request to the data
processing system 104. For example, the computing device can
include a microphone into which a user speaks the request. The
computing device can convert the microphone's recording into an
input audio signal that is transmitted to the data processing
system. The NLP component 110 can identify, in audio-based request,
a request and a trigger keyword that can correspond to the request.
A direct action application programming interface of the data
processing system 104, based on at least one of the request and the
trigger keyword, can generate a first action data structure. For
example, the NLP component 110 can parse the input audio signal to
identify requests that relate to subject matter of the input audio
signal, or to identify trigger keywords that can indicate, for
example, actions associated with the requests.
[0129] The method 600 can include receiving selection criteria (ACT
604). The selection criteria can include device identifier
characteristics. The selection criteria can be associated with a
digital component. The device identifier characteristics can be an
indication of a device identifier. The device identifier
characteristics can be characteristics of a computing device the
service provider computing device 160 or the content provider
computing device 108 is interested having digital components
transmitted. The device identifier characteristics can include
display screen parameters (e.g., size, resolution), audio
parameters, mobile device parameters, (e.g., processing power,
battery life, existence of installed apps or programs, or sensor
151 or speaker 154 capabilities), content slots on online documents
for text, image, or video renderings of content items, chat
applications, laptops parameters, smartwatch or other wearable
device parameters (e.g., indications of their display or processing
capabilities), or virtual reality headset parameters.
[0130] The method 600 can include identifying a plurality of
digital components (ACT 606). The plurality of digital components
can be associated with the digital component with which the
selection criteria are associated. The plurality of digital
components can be digital components that are related to the
digital component identified in the characteristics. For example,
the plurality of digital components can be provided by the same
service provider computing device 160, the same content provider
computing device 108, or can include the same or related subject
matter. The data processing system 104 can identify the plurality
of digital components through a lookup table. The related digital
components can be stored in a relational database that enables the
retrieval of related digital components.
[0131] The method 600 can include determining a count (ACT 608).
The count can represent a number of the plurality of digital
components previously transmitted to the computing device. The data
processing system can determine the number of times one of the
plurality of digital components was transmitted to the computing
device for display on the computing device. The count can represent
a number of times the plurality of digital components were
transmitted to the computing device within past time interval. For
example, the number of times in the last month, week, day, or
hour.
[0132] The method 600 can include receiving a target number (ACT
610). The target number can indicate a target count for the number
of times digital components from the plurality of digital
components are to be transmitted to the computing device within a
predetermined time interface. The time interval can be an hour,
day, week, plurality of weeks, month, or plurality of months.
[0133] The method 600 can include determining a probability (ACT
612). The probability can be the probability the count reaches the
target number within a predetermined time interval. The probability
can be based on the type or characteristic of the digital
component. The data processing system can select an exposure model.
The data processing system can use the selected exposure model to
determine the probability the count reaches the target number. The
data processing system can also identify an exposure interval that
can be on the selection criteria. The exposure interval can
indicate a target amount of time the digital component is displayed
to on a computing device. For example, the display or rendering of
a digital component can be terminate by a user prior to the digital
component being displayed for the length of time indicated by the
exposure interval. The second probability can indicate the
probability the digital component will be displayed for the full
exposure interval prior to the display of the digital component
being termination by a user.
[0134] In some implementations, the data processing system 104 can
determine a second count that indicates the number to times the
plurality of digital component were transmitted to a second
computing device that is associated with the computing device that
transmitted the request to the data processing system. The second
computing device can be a computing device that is linked to the
computing device that transmitted the request by a common login or
by a grouping that is established by the user of the computing
device. The data processing system can calculate a second
probability that a combination of the count and the second count
reaches the target number with the predetermined time interval. The
second probability can be the probability that the display of the
digital component on the combination of both the computing device
and the second computing device reaches the target number.
[0135] The method 600 can include selecting a candidate digital
component (ACT 614). The data processing system can select the
candidate digital component based on the probability and selection
criteria. The candidate digital component can be selected based on
the probability and the probability that the candidate digital
component will be exposed for the predetermined exposure interval.
The candidate digital component can be selected based on the
probability and the probability that the candidate digital
component (or related digital components) are displayed on a
combination of the computing device and the second computing device
the target number of times. The candidate digital component can be
selected by the data processing system based on the first action
data structure. In some implementations, the data processing system
can determine not to select a digital component as a candidate
digital component if the probability is below a predetermined
threshold. For example, if the data processing system determines
the probability of reaching the target number is low, the data
processing system can select to not select and transmit a digital
component to the computing device. The data processing system can
determine not to transmit a selected digital component to the
computing device because the transmission of the digital component
would be a waste of computational resources and bandwidth.
[0136] The method 600 can include transmitting the candidate
digital component (ACT 616). The data processing system can
transmit the candidate digital component to the computing device.
The data processing system can select to transmit the digital
component to a second computing device that is related to the
computing device. The data processing system can include an
interface management component that can poll a plurality of
interfaces to identify a first candidate interface of the computing
device and a second candidate interface of a second computing
device. The interface management component can determine resource
utilization values for each of the candidate interfaces. The
resources utilization values can be based on at least one of a
battery status, processor utilization, memory utilization, an
interface parameter, and network bandwidth utilization. The
interface management component can select to transmit the candidate
digital component to the computing device based on the first
resource utilization value and the second resource utilization
value. For example, the data processing system can select to which
candidate interface to transmit the digital component based on a
comparison of the remaining battery life and interface types (e.g.,
screen or speaker interfaces) available at each of the first and
second candidate interfaces. In some implementations, the data
processing system can transmit the digital component to the second
candidate interface in place of the first candidate interface. The
data processing system can transmit the digital component to both
the first and the second candidate interfaces. The candidate
interfaces can be interfaces of a single computing device or of
multiple, different computing devices. For example, the first
candidate interface can be a screen of a first computing device and
the second candidate interface can be a speaker of the first
computing device. The second candidate interface can be a type of
interface a first computing device does not have. For example, a
first computing device may not have a screen and second candidate
interface can be a screen interface of a second computing device
related to the first computing device. In some implementations, the
interface management component can determine a distance between
each of the plurality of candidate interfaces and the computing
device that transmitted the request to the data processing system.
The data processing system can select the candidate digital
component based on the distance between each of the plurality of
candidate interfaces and the computing device. The interfaces can
include a display screen, an audio interface, a vibration
interface, an email interface, a push notification interface, a
mobile computing device interface, a portable computing device
application, a content slot on an online document, a chat
application, mobile computing device application, a laptop, a
watch, a virtual reality headset, and a speaker.
[0137] FIG. 7 is a block diagram of an example computer system 700.
The computer system or computing device 700 can include or be used
to implement the system 100, or its components such as the data
processing system 104. The computing system 700 includes a bus 705
or other communication component for communicating information and
a processor 710 or processing circuit coupled to the bus 705 for
processing information. The computing system 700 can also include
one or more processors 710 or processing circuits coupled to the
bus for processing information. The computing system 700 also
includes main memory 715, such as a random access memory (RAM) or
other dynamic storage device, coupled to the bus 705 for storing
information, and instructions to be executed by the processor 710.
The main memory 715 can be or include the data repository 145. The
main memory 715 can also be used for storing position information,
temporary variables, or other intermediate information during
execution of instructions by the processor 710. The computing
system 700 may further include a read only memory (ROM) 720 or
other static storage device coupled to the bus 705 for storing
static information and instructions for the processor 710. A
storage device 725, such as a solid state device, magnetic disk or
optical disk, can be coupled to the bus 705 to persistently store
information and instructions. The storage device 725 can include or
be part of the data repository 145.
[0138] The computing system 700 may be coupled via the bus 705 to a
display 735, such as a liquid crystal display, or active matrix
display, for displaying information to a user. An input device 730,
such as a keyboard including alphanumeric and other keys, may be
coupled to the bus 705 for communicating information and command
selections to the processor 710. The input device 730 can include a
touch screen display 735. The input device 730 can also include a
cursor control, such as a mouse, a trackball, or cursor direction
keys, for communicating direction information and command
selections to the processor 710 and for controlling cursor movement
on the display 735. The display 735 can be part of the data
processing system 104, the client computing device 102 or other
component of FIG. 1A and FIG. 1B, for example.
[0139] The processes, systems and methods described herein can be
implemented by the computing system 700 in response to the
processor 710 executing an arrangement of instructions contained in
main memory 715. Such instructions can be read into main memory 715
from another computer-readable medium, such as the storage device
725. Execution of the arrangement of instructions contained in main
memory 715 causes the computing system 700 to perform the
illustrative processes described herein. One or more processors in
a multi-processing arrangement may also be employed to execute the
instructions contained in main memory 715. Hard-wired circuitry can
be used in place of or in combination with software instructions
together with the systems and methods described herein. Systems and
methods described herein are not limited to any specific
combination of hardware circuitry and software.
[0140] Although an example computing system has been described in
FIG. 7, the subject matter including the operations described in
this specification can be implemented in other types of digital
electronic circuitry, or in computer software, firmware, or
hardware, including the structures disclosed in this specification
and their structural equivalents, or in combinations of one or more
of them.
[0141] For situations in which the systems discussed herein collect
personal information about users, or may make use of personal
information, the users may be provided with an opportunity to
control whether programs or features that may collect personal
information (e.g., information about a user's social network,
social actions or activities, a user's preferences, or a user's
location), or to control whether or how to receive content from a
content server or other data processing system that may be more
relevant to the user. In addition, certain data may be anonymized
in one or more ways before it is stored or used, so that personally
identifiable information is removed when generating parameters. For
example, a user's identity may be anonymized so that no personally
identifiable information can be determined for the user, or a
user's geographic location may be generalized where location
information is obtained (such as to a city, postal code, or state
level), so that a particular location of a user cannot be
determined. Thus, the user may have control over how information is
collected about him or her and used by the content server.
[0142] The subject matter and the operations described in this
specification can be implemented in digital electronic circuitry,
or in computer software, firmware, or hardware, including the
structures disclosed in this specification and their structural
equivalents, or in combinations of one or more of them. The subject
matter described in this specification can be implemented as one or
more computer programs, e.g., one or more circuits of computer
program instructions, encoded on one or more computer storage media
for execution by, or to control the operation of, data processing
apparatuses. Alternatively or in addition, the program instructions
can be encoded on an artificially generated propagated signal,
e.g., a machine-generated electrical, optical, or electromagnetic
signal that is generated to encode information for transmission to
suitable receiver apparatus for execution by a data processing
apparatus. A computer storage medium can be, or be included in, a
computer-readable storage device, a computer-readable storage
substrate, a random or serial access memory array or device, or a
combination of one or more of them. While a computer storage medium
is not a propagated signal, a computer storage medium can be a
source or destination of computer program instructions encoded in
an artificially generated propagated signal. The computer storage
medium can also be, or be included in, one or more separate
components or media (e.g., multiple CDs, disks, or other storage
devices). The operations described in this specification can be
implemented as operations performed by a data processing apparatus
on data stored on one or more computer-readable storage devices or
received from other sources.
[0143] The terms "data processing system" "computing device"
"component" or "data processing apparatus" encompass various
apparatuses, devices, and machines for processing data, including
by way of example a programmable processor, a computer, a system on
a chip, or multiple ones, or combinations of the foregoing. The
apparatus can include special purpose logic circuitry, e.g., an
FPGA (field programmable gate array) or an ASIC (application
specific integrated circuit). The apparatus can also include, in
addition to hardware, code that creates an execution environment
for the computer program in question, e.g., code that constitutes
processor firmware, a protocol stack, a database management system,
an operating system, a cross-platform runtime environment, a
virtual machine, or a combination of one or more of them. The
apparatus and execution environment can realize various different
computing model infrastructures, such as web services, distributed
computing and grid computing infrastructures. The interface
management component 140, direct action API 135, content selector
component 125, prediction component 120 or NLP component 110 and
other data processing system 104 components can include or share
one or more data processing apparatuses, systems, computing
devices, or processors.
[0144] A computer program (also known as a program, software,
software application, app, script, or code) can be written in any
form of programming language, including compiled or interpreted
languages, declarative or procedural languages, and can be deployed
in any form, including as a stand-alone program or as a module,
component, subroutine, object, or other unit suitable for use in a
computing environment. A computer program can correspond to a file
in a file system. A computer program can be stored in a portion of
a file that holds other programs or data (e.g., one or more scripts
stored in a markup language document), in a single file dedicated
to the program in question, or in multiple coordinated files (e.g.,
files that store one or more modules, sub-programs, or portions of
code). A computer program can be deployed to be executed on one
computer or on multiple computers that are located at one site or
distributed across multiple sites and interconnected by a
communication network.
[0145] The processes and logic flows described in this
specification can be performed by one or more programmable
processors executing one or more computer programs (e.g.,
components of the data processing system 104) to perform actions by
operating on input data and generating output. The processes and
logic flows can also be performed by, and apparatuses can also be
implemented as, special purpose logic circuitry, e.g., an FPGA
(field programmable gate array) or an ASIC (application-specific
integrated circuit). Devices suitable for storing computer program
instructions and data include all forms of non-volatile memory,
media and memory devices, including by way of example semiconductor
memory devices, e.g., EPROM, EEPROM, and flash memory devices;
magnetic disks, e.g., internal hard disks or removable disks;
magneto optical disks; and CD ROM and DVD-ROM disks. The processor
and the memory can be supplemented by, or incorporated in, special
purpose logic circuitry.
[0146] The subject matter described herein can be implemented in a
computing system that includes a back-end component, e.g., as a
data server, or that includes a middleware component, e.g., an
application server, or that includes a front-end component, e.g., a
client computer having a graphical user interface or a web browser
through which a user can interact with an implementation of the
subject matter described in this specification, or a combination of
one or more such back-end, middleware, or front-end components. The
components of the system can be interconnected by any form or
medium of digital data communication, e.g., a communication
network. Examples of communication networks include a local area
network ("LAN") and a wide area network ("WAN"), an inter-network
(e.g., the Internet), and peer-to-peer networks (e.g., ad hoc
peer-to-peer networks).
[0147] The computing system such as system 100 or system 700 can
include clients and servers. A client and server are generally
remote from each other and typically interact through a
communication network (e.g., the network 106). The relationship of
client and server arises by virtue of computer programs running on
the respective computers and having a client-server relationship to
each other. In some implementations, a server transmits data (e.g.,
data packets representing action data structures or content items)
to a client device (e.g., to the client computing device 102 for
purposes of displaying data to and receiving user input from a user
interacting with the client device, or to the service provider
computing device 160 or the content provider computing device 108).
Data generated at the client device (e.g., a result of the user
interaction) can be received from the client device at the server
(e.g., received by the data processing system 104 from the
computing device 102 or the content provider computing device 108
or the service provider computing device 160).
[0148] While operations are depicted in the drawings in a
particular order, such operations are not required to be performed
in the particular order shown or in sequential order, and all
illustrated operations are not required to be performed. Actions
described herein can be performed in a different order.
[0149] The separation of various system components does not require
separation in all implementations, and the described program
components can be included in a single hardware or software
product. For example, the NLP component 110, the content selector
component 125, the interface management component 140, or the
prediction component 120 can be a single component, app, or
program, or a logic device having one or more processing circuits,
or part of one or more servers of the data processing system
104.
[0150] Having now described some illustrative implementations, it
is apparent that the foregoing is illustrative and not limiting,
having been presented by way of example. In particular, although
many of the examples presented herein involve specific combinations
of method acts or system elements, those acts and those elements
may be combined in other ways to accomplish the same objectives.
Acts, elements and features discussed in connection with one
implementation are not intended to be excluded from a similar role
in other implementations or implementations.
[0151] The phraseology and terminology used herein is for the
purpose of description and should not be regarded as limiting. The
use of "including" "comprising" "having" "containing" "involving"
"characterized by" "characterized in that" and variations thereof
herein, is meant to encompass the items listed thereafter,
equivalents thereof, and additional items, as well as alternate
implementations consisting of the items listed thereafter
exclusively. In one implementation, the systems and methods
described herein consist of one, each combination of more than one,
or all of the described elements, acts, or components.
[0152] Any references to implementations or elements or acts of the
systems and methods herein referred to in the singular may also
embrace implementations including a plurality of these elements,
and any references in plural to any implementation or element or
act herein may also embrace implementations including only a single
element. References in the singular or plural form are not intended
to limit the presently disclosed systems or methods, their
components, acts, or elements to single or plural configurations.
References to any act or element being based on any information,
act or element may include implementations where the act or element
is based at least in part on any information, act, or element.
[0153] Any implementation disclosed herein may be combined with any
other implementation or embodiment, and references to "an
implementation," "some implementations," "one implementation" or
the like are not necessarily mutually exclusive and are intended to
indicate that a particular feature, structure, or characteristic
described in connection with the implementation may be included in
at least one implementation or embodiment. Such terms as used
herein are not necessarily all referring to the same
implementation. Any implementation may be combined with any other
implementation, inclusively or exclusively, in any manner
consistent with the aspects and implementations disclosed
herein.
[0154] References to "or" may be construed as inclusive so that any
terms described using "or" may indicate any of a single, more than
one, and all of the described terms. For example, a reference to
"at least one of `A` and `B`" can include only `A`, only `B`, as
well as both `A` and `B`. Such references used in conjunction with
"comprising" or other open terminology can include additional
items.
[0155] Where technical features in the drawings, detailed
description or any claim are followed by reference signs, the
reference signs have been included to increase the intelligibility
of the drawings, detailed description, and claims. Accordingly,
neither the reference signs nor their absence have any limiting
effect on the scope of any claim elements.
[0156] The systems and methods described herein may be embodied in
other specific forms without departing from the characteristics
thereof. The foregoing implementations are illustrative rather than
limiting of the described systems and methods. Scope of the systems
and methods described herein is thus indicated by the appended
claims, rather than the foregoing description, and changes that
come within the meaning and range of equivalency of the claims are
embraced therein.
* * * * *